1. Field of the Related Art
The present disclosure relates to fingerprint recognition technology, and more particularly, but not exclusively, to methods and systems for automated fingerprint recognition, collection, transmission, reception, and storage at points-of-sale and/or points-of-entry, such as retail/grocery stores and entertainment venues.
2. Description of the Related Art
The need to identify and authenticate individuals is greater today than it has ever been, and is particularly acute for applications such as homeland security, law enforcement, electronic commerce, access control and privacy protection, to name a few.
The use of biometrics in general, and fingerprint recognition in particular, to identify and authenticate humans is a proven method. Biometrics is a group of technologies that provide a high level of security. Fingerprint capture and recognition is an important biometric technology. Law enforcement, banking, voting, and other industries increasingly rely upon fingerprints as a biometric to recognize or verify identity.
Fingerprint identification systems involve the use of a computer, which provides an identification probability for a match of a fingerprint to a prerecorded fingerprint held in a database. In this manner, fingerprint recognition devices have been employed for accessing high security areas. Fingerprint scanners are one form of fingerprint recognition devices. Fingerprint scanners having image sensors are available, which capture an image off a fingerprint. A signal representative of the captured image is then sent over a data communication interface to a host computer for further processing. For example, the host computer may perform one-to-one or one-to-many fingerprint matching.
Additionally, with crime in the United States and elsewhere on the upswing and with the relative supply of trained law enforcement personnel on the decline, the law enforcement community has been forced, in recent years, to investigate and consider the automatic processing of the large amounts of data it is required to maintain. One area of recent interest has been in the automatic processing of fingerprints.
Evidence from criminal activities and criminal suspects has long been analyzed to assist law enforcement officials in their attempts to determine who carried out a particular crime. Fingerprint identification is one of the oldest forms of forensic analysis of a crime scene. Fingerprints are often collected and analyzed in order to identify individuals who were at the scene of the crime or who have committed prior crimes. The fingerprints that are gathered may be compared with the prints of known individuals. Large numbers of fingerprints are collected and stored everyday in a wide range of applications including forensics, access control, and driver license registration. These fingerprints are kept on file and used to help law enforcement officials identify suspects, in modern times, computers have made it easy to compare a single fingerprint with a large number of fingerprints.
However, to perform identification and authentication in many of the applications envisaged today, collection of several samples of fingerprints in various environments is important. Thus, there is a need for automated (computer-assisted) fingerprint recognition, where a large number of fingerprints may be collected from various environments without sacrificing accuracy. Thus, there is a need in the fingerprint recognition art for a technological solution that overcomes at least in part the aforesaid deficiencies.